Asian-Pacific Countries Comparison

load("./data/wine150_tidy")

wine150_tidy %>% 
  select(country, points_avg_country) %>% 
  filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>% 
  mutate(country = fct_reorder(country, desc(points_avg_country))) %>% 
  unique() %>% 
  mutate(text_label = str_c("Country: ", country, "\nAverage Points: ", points_avg_country)) %>% 
  plot_ly(
    x = ~country, y = ~points_avg_country, color = ~factor(country), text = ~text_label,
    type = "bar", colors = "viridis") %>%
  layout(
    xaxis = list(title = "Asian-Pacific Countries"),
    yaxis = list(title = "Average Wine Points", range = (c(80,88))),
    title = "Average Wine Points of Asian-Pacific Countries")


Top 20 Asian-Pacific Wineries

load("./data/wine150_tidy")

wine150_tidy %>% 
  select(points, country, winery, variety, points_avg_variety, points_avg_winery) %>% 
  filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>% 
  mutate(winery = fct_reorder(winery, desc(points_avg_winery))) %>% 
  filter(as.numeric(winery) <= 20) %>% 
  arrange(winery) %>% 
  plot_ly(
    x = ~winery, y = ~points, color = ~factor(winery),
    type = "box", colors = "viridis") %>%
  layout(
    xaxis = list(title = "Asian-Pacific Wineries"),
    yaxis = list(title = "Wine Points"),
    title = "Top 20 Asian-Pacific Wineries: Highest Professional Recognition")


Bottom 20 Asian-Pacific Wineries

load("./data/wine150_tidy")

wine150_tidy %>% 
  select(points, country, winery, variety, points_avg_variety, points_avg_winery) %>% 
  filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>% 
  mutate(winery = fct_reorder(winery, points_avg_winery)) %>% 
  filter(as.numeric(winery) <= 20) %>% 
  arrange(winery) %>% 
  plot_ly(
    x = ~winery, y = ~points, color = ~factor(winery),
    type = "box", colors = "viridis") %>%
  layout(
    xaxis = list(title = "Asian-Pacific Wineries"),
    yaxis = list(title = "Wine Points"),
    title = "Bottom 20 Asian-Pacific Wineries: Lowest Professional Recognition")


Top 10 Grapes for Asian-Pacific Wines

load("./data/wine150_tidy")

wine150_tidy %>% 
  select(points, country, winery, variety, points_med_variety, points_med_winery) %>% 
  filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>% 
  mutate(variety = fct_reorder(variety, desc(points_med_variety))) %>% 
  filter(as.numeric(variety) <= 10) %>% 
  arrange(variety) %>% 
  plot_ly(
    x = ~variety, y = ~points, color = ~factor(variety),
    type = "violin", colors = "viridis") %>%
  layout(
    xaxis = list(title = "Grapes for Asian-Pacific Wines"),
    yaxis = list(title = "Wine Points"),
    title = "Most Favorable 10 Grapes for Asian-Pacific Wines: Highest Professional Recognition")


Bottom 10 Grapes for Asian-Pacific Wines

load("./data/wine150_tidy")

wine150_tidy %>% 
  select(points, country, winery, variety, points_med_variety, points_med_winery) %>% 
  filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>% 
  mutate(variety = fct_reorder(variety, points_med_variety)) %>% 
  filter(as.numeric(variety) <= 10) %>% 
  arrange(variety) %>% 
  plot_ly(
    x = ~variety, y = ~points, color = ~factor(variety),
    type = "violin", colors = "viridis") %>%
  layout(
    xaxis = list(title = "Grapes for Asian-Pacific Wines"),
    yaxis = list(title = "Wine Points"),
    title = "Least Favorable 10 Grapes for Asian-Pacific Wines: Lowest Professional Recognition")